This disclosure relates generally to the field of determining subsurface structures from passive seismic signals. More specifically, the disclosure relates to methods for determining total volume of formation stimulated by networks of rock formation fractures using passive seismic signals. A propped fracture network volume may be used, for example, to estimate expected ultimate recovery from a fractured reservoir.
The performance of a subsurface reservoir is related to, among other factors, the spatial distribution of permeability in the reservoir. Methods are known in the art for estimating permeability distribution for “matrix” permeability, that is, permeability resulting from interconnections between the pore spaces of porous rock formations. Another type of permeability that is present in some reservoirs, and has proven more difficult to simulate the permeability distribution thereof is so called “fracture” permeability. Fracture permeability is associated with breaks or fractures in the rock formation. Fractures may be caused by rock that is stimulated by fractures held open by proppant pumped into the formation through a wellbore with fluid under pressure until the fracture pressure of the formation is exceeded. After pumping, the proppant remains in the fractures and holds them open to create high permeability fluid flow paths from relatively large lateral distances from the wellbore, thus increasing available reservoir drainage volume. Fractures are also known to be present naturally in some rock formations.
Microseismicity induced by reservoir stimulation of the geothermal field has been used to map fracture density. See, Lees, J. M., 1998, Multiplet analyses at Coso geothermal: Bulletin of The Seismological Society of America, 88, 1127-1143. In the Lees publication, a downhole monitoring array of several geophones was used to locate and invert source mechanisms, which provide estimates of fracture orientation. Density of the located events was then used to constrain the fracture density in a reservoir model.
Source mechanism inversion is described in, Jost and Herman, 1989, Seismological Research Letters, Vol. 60, pp 37-57, and in Aki and Richards, Quantitative Seismology, 1980.
Methods for modeling discrete fracture networks are described by Dershowitz, W., and Herda, H., 1992, Interpretation of fracture spacing and intensity, in Rock Mechanics, J. R. Tillerson and W. R. Wawersik (eds.), Balkema, Rotterdam, p. 757-766, and La Point P. R., Hermanson J., Thorsten E., Dunleavy M., Whitney J. and Eubanks D. 2001. 3-D reservoir and stochastic fracture network modelling for enhanced oil recovery, Circle Ridge Phospohoria/Tensleep Reservoir, Wind River Reservation, Arapaho and Shoshone Tribes, Wyoming: Golder Associates Inc., Report DE-FG26-00BC15190, Dec. 7, 2001, 63 p. Several commercial software packages are available that use these methods to generate fracture models. To do reservoir simulation, the fracture networks are used to calculate flow properties given a particular fracture network configuration. One of many methods for calculating fracture permeability is described in Oda, M. 1985, Permeability Tensor for Discontinuous Rock Masses, Geotechnique Vol. 35, p 483.